Artificial Intelligence and Machine Learning In Commerce: A Comprehensive Study on Adoption, Challenges, And Future Prospects

Abstract

The rapid diffusion of Artificial Intelligence (AI) and Machine Learning (ML) technologies is reshaping the commerce and retail landscape, altering how firms forecast demand, personalise customer experience, price products, manage inventory, and detect fraud. This study examines the drivers, barriers, and future trajectory of AI/ML adoption in commerce through a quantitative, cross-sectional survey of 410 respondents comprising retail and e-commerce managers, business owners, and technology decision-makers. Grounded in an integrated framework combining the Technology Acceptance Model (TAM) and the Technology-Organisation-Environment (TOE) framework, the study tests relationships among Perceived Usefulness, Perceived Ease of Use, Organisational Readiness, Technological Challenges, Behavioural Intention, and actual AI/ML Adoption. Data were analysed using IBM SPSS 27 for descriptive and reliability statistics and AMOS 26 / SmartPLS 4 for confirmatory factor analysis (CFA) and structural equation modelling (SEM). Results indicate that Perceived Usefulness (β = 0.34, p < 0.001), Organisational Readiness (β = 0.29, p < 0.001), and Behavioural Intention (β = 0.41, p < 0.001) are the strongest predictors of AI/ML adoption, while Technological Challenges exert a significant negative influence (β = -0.22, p < 0.01). The measurement model demonstrated satisfactory reliability and validity (Cronbach's α > 0.80 for all constructs; AVE > 0.50; CR > 0.70), and the structural model showed acceptable fit (CMIN/df = 2.14, CFI = 0.951, RMSEA = 0.052). The study concludes that successful AI/ML adoption in commerce depends jointly on perceived business value and organisational capability, while data quality, cost, and skill shortages remain the most persistent barriers. Implications for practitioners, policymakers, and researchers are discussed, along with a research agenda for generative AI and agentic commerce technologies.